Video analysis system

ABSTRACT

A video analysis system includes: a video data acquiring means that acquires video data; a moving object detecting means that detects a moving object from video data acquired by the video data acquiring means, by using a moving object detection parameter, which is a parameter for detecting a moving object; an environment information collecting means that collects environment information representing an external environment of a place where the video data acquiring means is installed; and a parameter changing means that changes the moving object detection parameter used when the moving object detecting means detects a moving object, on the basis of the environment information collected by the environment information collecting means.

The present application is a Continuation application of Ser. No.15/117,814 filed on Aug. 10, 2016, which is a National Stage Entry ofPCT/JP2015/000529 filed on Feb. 5, 2015, which claims priority fromJapanese Patent Application 2014-026465 filed on Feb. 14, 2014, thecontents of all of which are incorporated herein by reference, in theirentirety.

TECHNICAL FIELD

The present invention relates to a video analysis system, a videoanalysis device, a video analysis method, and a program

BACKGROUND ART

There is a known video analysis system which includes a monitoringcamera to be installed and monitors a moving object such as a personmoving in a monitored area for the purpose of crime prevention, disasterprevention, and so on. For example, it is proposed as a first relatedtechnique relating to the present invention to compare a frame image ofa video image shot by a monitoring camera with a last frame image,extract a difference between the frame images, and detect a movingobject such as an intruder based on the extracted difference (see PatentDocument 1, for example).

On the other hand, the following techniques are proposed as othertechniques relating to the present invention.

First, it is proposed as a second related technique relating to thepresent invention to acquire camera information and related informationwhich are acquired or inputted in shooting an image, estimate the sceneof the image by using the camera information and the relatedinformation, and execute predetermined image processing appropriate tothe estimated image scene (see Patent Document 2, for example).According to this second related technique, it is possible to correctdata of a shot image in accordance with a shooting environment andincrease the quality of the image.

Further, the following image correction system is proposed as a thirdrelated technique relating to the present invention. The imagecorrection system includes an information acquisition part whichacquires state information showing a state in which a photograph hasbeen shot, a correction parameter selection part which selects aplurality of correction parameters based on the state information, andan image quality correction part which executes an image data correctionprocess by using the selected correction parameters. According to thethird related technique, it is possible to alter the quality of a shotimage in accordance with a shooting environment.

Patent Document 1: Japanese Unexamined Patent Application PublicationNo. JP-A 2011-077617Patent Document 2: Japanese Unexamined Patent Application PublicationNo. JP-A 2011-238177Patent Document 3: Japanese Unexamined Patent Application PublicationNo. JP-A 2010-171661

When a video analysis system as mentioned above is used, a monitoringcamera which acquires video data may be installed outdoors, for example,on the street or around the entrance. When the monitoring camera is thusinstalled outdoors, the environment of a place where the monitoringcamera is installed change under the influence of change of the outdoorenvironment. In other words, when the monitoring camera is installedoutdoors, the environment of the installation place greatly variesdepending on, for example, whether it is fine or rainy, whether it is inthe daytime or at night, and whether the wind is blowing or not. Whenthe environment of the place where the monitoring camera is installedchanges, video data acquired by the monitoring camera changes. Forexample, the shadow of a moving object is clearly shown on a fine day,but the shadow is not shown on a cloudy day. On a windy day, trees orthe like on the background largely swings.

Therefore, it is desired to prevent the accuracy of detection of amoving object from being affected even when the environment of a placewhere a monitoring camera is installed changes and video data changes.

In order to deal with such a problem, it is possible to considerapplying the second or third related technique to the first relatedtechnique and correcting data of a shot image in accordance with theshooting environment to increase or change the quality of the image.However, increase or alteration of the quality of an image does notnecessarily lead to increase of the analysis performance of a videoanalysis system. For example, when the quality of image data including aperson as a subject is increased by using the abovementioned techniques,a portion corresponding to the shadow of the person is also shownsharply. As a result, a video analysis system may falsely detect thesharply shown portion corresponding to the shadow of the person as amoving object. Thus, for a video analysis system, simple increase oralteration of the quality of an image does not always lead to increaseof the analysis performance.

Thus, a video analysis system has a problem that change of theenvironment of installation of a monitoring camera and change of videodata may affect the accuracy of detection of a moving object.

SUMMARY

Accordingly, an object of the present invention is to provide a videoanalysis system which solves the problem that change of the environmentof installation of a monitoring camera and change of video data mayaffect the accuracy of detection of a moving object.

In order to achieve the object, a video analysis system as an aspect ofthe present invention includes:

a video data acquiring means for acquiring video data;

a moving object detecting means for detecting a moving object from videodata by using a moving object detection parameter, the moving objectmoving in the video data, the video data having been acquired by thevideo data acquiring means, the moving object detection parameter beinga parameter for detecting a moving object;

an environment information collecting means for collecting environmentinformation representing an external environment of a place where thevideo data acquiring means is installed; and

a parameter changing means for changing the moving object detectionparameter on a basis of the environment information collected by theenvironment information collecting means, the moving object detectionparameter being used when the moving object detecting means detects themoving object.

Further, a video analysis device as another aspect of the presentinvention includes:

a video data acquisition part configured to acquire video data from anexternal device, the video data having been acquired by the externaldevice;

a moving object detection part configured to detect a moving object fromvideo data by using a moving object detection parameter, the movingobject moving in the video data, the video data having been acquired bythe video data acquisition part, the moving object detection parameterbeing a parameter for detecting a moving object;

an environment information collection part configured to collectenvironment information representing an external environment of a placewhere the external device having acquired the video data is installed;and

a parameter changing part configured to change the moving objectdetection parameter on a basis of the environment information collectedby the environment information collection part, the moving objectdetection parameter being used when the moving object detection partdetects the moving object.

Further, a video analysis method as another aspect of the presentinvention includes:

collecting environment information and changing a moving objectdetection parameter on a basis of the collected environment information,the environment information representing an external environment of aplace where an external device acquiring video data is installed, themoving object detection parameter being used when detecting a movingobject from the video data; and

detecting the moving object from the video data by using the changedmoving object detection parameter, the moving object moving in the videodata, the video data being acquired from the external device.

Further, a computer program including instructions for causing a videoanalysis device to function as:

a video data acquisition part configured to acquire video data from anexternal device, the video data being acquired by the external device;

a moving object detection part configured to detect a moving object fromvideo data by using a moving object detection parameter, the movingobject moving in the video data, the video data being acquired by thevideo data acquisition part, the moving object detection parameter beinga parameter for detecting a moving object;

an environment information collection part configured to collectenvironment information representing an external environment of a placewhere the external device having acquired the video data is installed;and

a parameter changing part configured to change the moving objectdetection parameter on a basis of the environment information acquiredby the environment information collection part, the moving objectdetection parameter being used when the moving object detection partdetects the moving object.

With the configurations as described above, the present inventionenables provision of a video analysis system in which change of theenvironment of installation of a monitoring camera or change of videodata do not affect the accuracy of detection of a moving object.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a view showing the configuration overview of a whole videoanalysis system according to a first exemplary embodiment of the presentinvention;

FIG. 2 is a block diagram showing the configuration of the videoanalysis system according to the first exemplary embodiment of thepresent invention;

FIG. 3 is a block diagram showing an example of the configuration of anenvironment information collecting means included by the video analysissystem according to the first exemplary embodiment of the presentinvention;

FIG. 4 is a view for describing an example of a moving object detectionparameter changed by a parameter changing means of a video analysisdevice shown in FIG. 2;

FIG. 5 is a view for describing an example of the moving objectdetection parameter changed by the parameter changing means of the videoanalysis device shown in FIG. 2;

FIG. 6 is a view for describing an example of the moving objectdetection parameter changed by the parameter changing means of the videoanalysis device shown in FIG. 2;

FIG. 7 is a view for describing an example of the moving objectdetection parameter changed by the parameter changing means of the videoanalysis device shown in FIG. 2;

FIG. 8 is a view for describing an example of the moving objectdetection parameter changed by the parameter changing means of the videoanalysis device shown in FIG. 2;

FIG. 9 is a flowchart showing an example of a process from acquisitionof video data to detection of a person in the video data by the videoanalysis system according to the first exemplary embodiment of thepresent invention;

FIG. 10 is a flowchart showing an example of a process for detecting aperson in video data by the video analysis system according to the firstexemplary embodiment of the present invention;

FIG. 11 is a flowchart showing an example of a process for changing amoving object detection parameter based on environment information bythe video analysis system according to the first exemplary embodiment ofthe present invention;

FIG. 12 is a block diagram showing the configuration of a video analysissystem according to a second exemplary embodiment of the presentinvention;

FIG. 13 is a flowchart showing an example of a process for changing amoving object detection parameter based on environment information bythe video analysis system according to the second exemplary embodimentof the present invention;

FIG. 14 is a block diagram showing the configuration overview of a videoanalysis system according to a third exemplary embodiment of the presentinvention; and

FIG. 15 is a block diagram showing the configuration overview of a videoanalysis device according to a fourth exemplary embodiment of thepresent invention.

Exemplary Embodiments

Next, the exemplary embodiments of the present invention will bedescribed in detail referring to the attached drawings.

First Exemplary Embodiment

Referring to FIG. 1, in a video analysis system 1 according to a firstexemplary embodiment of the present invention, a monitoring camera 2 (avideo data acquiring means) acquires video data. Next, a video analysisdevice 4 detects a moving object moving in the video data by using amoving object detection parameter. Also, the video analysis device 4acquires the trajectory of the moving object, and so on. Then, theresult of the detection by the video analysis device 4 is outputted toan output device such as a monitor. Thus, the video analysis system 1according to this exemplary embodiment is a system which analyzes videodata, recognizes moving objects in the video data, and monitors the flow(the traveling method, flow line, behavior, and so on) of the movingobjects. In this exemplary embodiment, as described later, a movingobject detection parameter used when the video analysis device 4 detectsa moving object in video data is properly changed based on environmentinformation collected by an environment information collecting means 3.Hereinafter, this exemplary embodiment will describe a video analysissystem 1 which detects a moving person in video data of video analysissystems 1 which detect moving objects.

Referring to FIG. 2, the video analysis system 1 according to the firstexemplary embodiment of the present invention has the monitoring camera2 (the video data acquiring means), the environment informationcollecting means 3, and the video analysis device 4. Further, the videoanalysis device 4 has a video analyzing means 41 (a moving objectdetecting means), a parameter changing means 42, and an analysis resultdisplaying means 43. The video analysis device 4 in this exemplaryembodiment is an information processing device which includes anarithmetic device and a storage device. The video analysis device 4realizes the respective functions described above by execution of aprogram stored in the storage device by the arithmetic device.

The monitoring camera 2 is installed at a predetermined position and hasa function of acquiring video data at the predetermined position wherethe monitoring camera 2 is installed. The monitoring camera 2 isinstalled, for example, at the airport, at an oil plant, and on thestreet, and is connected to the video analysis device 4 via an externalnetwork or the like. The monitoring camera 2 processes video dataacquired by the monitoring camera 2 into a predetermined format, andthereafter, transmits the video data to the video analyzing means 41included by the video analysis device 4 via the external network or thelike.

This exemplary embodiment will describe a case where the video analysissystem 1 includes one monitoring camera 2. However, the video analysissystem 1 according to this exemplary embodiment is not limited to thecase where the video analysis system 1 includes the one monitoringcamera 2. The video analysis system 1 may be configured to acquire videodata from a plurality of monitoring cameras 2. Further, the video dataacquiring means included by the video analysis system 1 is not limitedto a case of using the monitoring camera 2. The video analysis system 1may include any video data acquiring means which acquires video data,instead of the monitoring camera 2.

The environment information collecting means 3 has a function ofcollecting environment information representing the external environmentof a place where the monitoring camera 2 is installed. For example, thedate, time (daytime, night), weather information, and latitude andlongitude of a place where the monitoring camera 2 is installed areregarded as the external environment. The environment information isinformation for grasping the external environment of a place where themonitoring camera 2 is installed (i.e., a shooting environmentcondition).

Referring to FIG. 3, the environment information collecting means 3 has,for example, a calendar 31, a Web information collecting means 32, andvarious sensors 33 such as a GPS sensor, a heliograph, a rain gauge andan anemometer. The video analysis system 1 grasps the state of theshooting environment (the external environment) in the vicinity of themonitoring camera 2 by using the environment information collectingmeans 3. Among the various sensors 33, various physical sensors such asthe GPS sensor, the heliograph, the rain gauge and the anemometer needto be installed in the vicinity of the monitoring camera 2 acquiringvideo data. On the other hand, the calendar 31, the Web informationcollecting means 32, and so on, that are not the physical sensors do notalways need to be installed in the vicinity of the monitoring camera 2.In other words, (part of) the function as the environment informationcollecting means 3 may be included by the video analysis device 4 to bedescribed later.

The calendar 31 is used to collect information such as the sunrise, thesunset, the moon's age, and the culmination altitude. The Webinformation collecting means 32 is used to collect information such asweather forecast information and the presence or absence of any event onthe Internet. The various sensors 33 are used to grasp, for example, thetime, sunshine duration, rainfall, and wind speed of a place where themonitoring camera 3 is installed. To be specific, the environmentinformation collecting means 3 collects information such as the latitudeand longitude, the height and the time by using the GPS sensor, forexample. The environment information collecting means 3 collects asunshine duration by using a heliograph, a rainfall by using a raingauge, and a wind speed by using an anemometer, for example.

Thus, the environment information collecting means 3 collects variousinformation (environment information) for grasping the externalenvironment of the monitoring camera 2 by using the calendar 31, the Webinformation collecting means 32 and the various sensors 33, for example.Then, the environment information collecting means 3 transmits thevarious environment information collected thereby to the parameterchanging means 42 of the video analysis device 4.

The environment information collecting means 3 may be configured toacquire environment information by using a method other than theabovementioned one. For example, the environment information collectingmeans 3 can include a meteorological instrument other than theabovementioned ones. Alternatively, the environment informationcollecting means 3 do not need to include the calendar 31, the Webinformation collecting means 32 and the various sensors 33 all. Theenvironment information collecting means 3 only needs to be configuredto be capable of collecting information (environment information)necessary to grasp the external environment of a place where themonitoring camera 2 is installed.

The video analysis device 4 has a function of detecting a person movingin video data acquired by the monitoring camera 2 by using a movingobject detection parameter. The video analysis device 4 also has afunction of changing a moving object detection parameter based onenvironment information collected by the environment informationcollecting means 3.

As described above, the video analysis device 4 is an informationprocessing device which includes a storage device and an arithmeticdevice. The video analysis device 4 realizes the video analyzing means41, the parameter changing means 42 and the analysis result displayingmeans 43 by execution of a program stored in the storage device by thearithmetic device.

The video analyzing means 41 has a function of detecting a person movingin video data acquired by the monitoring camera 2 by using a movingobject detection parameter. The video analyzing means 41 also has afunction of acquiring the trajectory of the detected moving person, andso on. The video analyzing means 41 is connected with the monitoringcamera 2 via an external network or the like and acquires video dataacquired by the monitoring camera 2 from the monitoring camera 2. Then,the video analyzing means 41 detects a person moving in the acquiredvideo data by using a moving object detection parameter.

To be specific, the video analyzing means 41 in this exemplaryembodiment obtains a difference of image data extracted from video data,and thereby finds an unstill object. In other words, the video analyzingmeans 41 obtains a difference between image data of a previous frame (anintegration result) and image data of a current frame, and thereby findsan unstill object. Then, the video analyzing means 41 removes apredetermined object of the unstill objects as a moving object otherthan a detection target object (a person) from a detection target. Forexample, the video analyzing means 41 removes a moving object other thana person from a detection target by using a reciprocating object removalfilter, a shadow removal filter or the like to be described later.Moreover, the video analyzing means 41 is capable of grasping what theunstill object is (for example, whether the unstill object is a personor not) by using a technique such as pattern recognition. Thus, thevideo analyzing means 41 detects a person moving in the video data.Then, the video analyzing means 41 tracks the grasped person by using aparticle filter or the like, and acquires the trajectory of movement ofthe detected person. Further, the video analyzing means 41 transmits thedetected person and the trajectory of the movement of the detectedperson as the detection result to the analysis result displaying means43.

The abovementioned moving object detection parameter is used, forexample, when the video analyzing means 41 obtains a difference of imagedata to find an unstill object, and when the video analyzing means 41uses a filter for removing a moving object other than a person. Thedetails of the moving object detection parameter will be describedlater.

The parameter changing means 42 has a function of changing a movingobject detection parameter used when the video analyzing means 41detects a moving object in video data, by using environment informationacquired from the environment information collecting means 3. Theparameter changing means 42 is connected with the environmentinformation collecting means 3, and acquires environment informationcollected by the environment information collecting means 3. Theparameter changing means 42 changes a moving object detection parameterbased on (the external environment represented by) the acquiredenvironment information (for example, so as to make the moving objectdetection parameter optimum for the external environment).

Change of a moving object detection parameter by the parameter changingmeans 42 is carried out by using a parameter set, which is a set ofmoving object detection parameters previously determined in accordancewith a possible external environment, for example. The parameterchanging means 42 may be configured to change each moving objectdetection parameter so that the moving object detection parameterbecomes the most appropriate to the external environment represented bythe acquired environment information.

Thus, the parameter changing means 42 acquires environment informationfrom the environment information collecting means 3. Then, the parameterchanging means 42 changes a moving object detection parameter used whenthe video analyzing means 41 detects a moving object in video data,based on the acquired environment information.

The analysis result displaying means 43 is connected to the outputdevice such as the monitor. The analysis result displaying means 43acquires an analysis result of analysis by the video analyzing means 41(a person, the trajectory of movement of the person, and so on, as theresult of the detection) from the video analyzing means 41. The analysisresult displaying means 43 then causes the output device such as themonitor to display the analysis result.

That is the configuration of the video analysis system 1. Meanwhile, thevideo analysis system 1 (for example, the video analysis device 4thereof) may include an analysis result accumulating means for storingthe results of analysis by the video analyzing means 41, and a videodata accumulating means for storing video data. Moreover, the videoanalysis system 1 can include an operation checking means for checking asystem operation using a moving object detection parameter changed bythe abovementioned configuration, and a parameter regulating means forautonomously conducting fine regulation of a moving object detectionparameter in response to the check of the operation by the operationchecking means.

Next, the details of the abovementioned moving object detectionparameter will be described with some specific examples.

A moving object detection parameter is a parameter used when the videoanalyzing means 41 detects a moving object in video data. As describedabove, a moving object detection parameter is used, for example, whenthe video analyzing means 41 obtains a difference of image data to findan unstill object, and when the video analyzing means 41 uses a filterfor removing a moving object other than a person. A moving objectdetection parameter is a sensitivity threshold, a moving objectdistinction threshold such as a reciprocating object removal thresholdand a shadow removal threshold, and so on.

A sensitivity threshold is one of the moving object detection parametersand is a threshold which is the criterion for recognizing a differencebetween image data of a previous frame and image data of a currentframe. In other words, a sensitivity threshold is a threshold used forrecognizing a moving object (an unstill object).

Describing specifically, when detecting a difference between image dataof a previous frame and image data of a current frame, the videoanalyzing means 41 detects a disparity between image data of a previousframe and image data of a current frame every minimum unit, for example,every pixel. A sensitivity threshold is a threshold for determining thedegree of change of the minimum unit for recognizing that (a certainminimum unit of) image data of a current frame has changed from (acertain minimum unit of) image data of a previous frame. In other words,a sensitivity threshold is the criterion for determining how to dealwith a disparity between image data of a previous frame and image dataof a current frame when detecting the disparity (i.e., determiningwhether or not image data has changed).

The video analysis system 1 according to this exemplary embodimentchanges the sensitivity threshold described above based on environmentinformation collected by the environment information collecting means.Referring to FIG. 4, a sensitivity threshold used when the videoanalyzing means 41 detects a moving object in video data can bedifferentiated, for example, between a light place (in the daytime, on afine day, and so on) and a dark place (at night, on a cloudy day, and soon). In other words, a sensitivity threshold can be changed inaccordance with environment information such as the time, luminance andweather collected by the environment information collecting means 3. Itis assumed that the monitoring camera 2 acquires video data in a lightplace and, therefore, a sensitivity threshold is set so that change ofthe minimum unit is recognized at a point when a while color turns to agray color (i.e., so that a change is detected with a wide disparityrange to some degree). Moreover, it is assumed that, in the abovecondition, time passes by and it gets dark at night in a place where themonitoring camera 2 is installed. In this case, if the sensitivitythreshold for the light place is still used, it may be impossible when,for example, a person wearing navy clothes is moving to detect theperson well because the person is under the cover of darkness. In otherwords, because contrast is generally small when it is dark such as atnight, there is a case where a change cannot be accurately detected if asensitivity threshold for a daytime is used. Therefore, when theenvironment information collecting means 3 collects environmentinformation such as a night time, the parameter changing means 42 of thevideo analysis system 1 changes a sensitivity threshold based on thecollected environment information. For example, when the environmentinformation collecting means 3 collects environment information of anight time, the parameter changing means 42 changes a sensitivitythreshold so that a change of the minimum unit is recognized at a pointwhen a white color turns to a light gray color (i.e., so that a changeis detected by a little disparity). Consequently, it becomes possible toaccurately detect a small change and, for example, it becomes possibleto detect a person wearing navy clothes without any problem even whenthe person is moving at night.

A moving object distinction threshold is one of the moving objectdetection parameters as well as a sensitivity threshold. A moving objectdistinction threshold is a threshold which is the criterion used when afilter for removing a moving object other than a detection target object(a person) from a detection target distinguishes a person (a detectiontarget object) from a moving object other than the person (other thanthe detection target object). Referring to FIG. 5, it is found that thevideo analyzing means 41 possibly detects, other than a person as thetarget of detection, a swinging tree and grass, shadow or the like asmoving objects. It is anticipated that detecting all the moving objectsand checking what all the detected moving objects are needs execution ofa large number of processes and the processing gets heavy. Therefore,the video analyzing means 41 executes processing so as to detect amoving object other than a person as a moving object as little aspossible, by using a predetermined filter for removing a moving objectother than a person of a detection target object. For example, areciprocating object removal filter, a shadow removal filter and thelike are regarded as the predetermined filter. Moreover, for example, areciprocating object removal threshold, a shadow removal threshold andthe like are regarded as a moving object distinction threshold.

A reciprocating object removal filter is a filter which regards areciprocating object conducting a predetermined reciprocation of arepeating movement as a moving object other than a person to become adetection target and excludes the reciprocating object from thedetection target. Moreover, a reciprocating object removal threshold isa threshold which is the criterion used when the reciprocating objectremoval filter distinguishes a person from a reciprocating object. Forexample, a tree, grass and electric line swung by wind are thought asreciprocating objects. Movement of the reciprocating object is differentfrom movement of a person having irregular vectors. Therefore, it ispossible to exclude such a reciprocating object, namely, a moving objectother than a person to be a detection target from the detection target.A reciprocating object removal threshold is, for example, a thresholdappropriate to the swing width and frequency of reciprocation.

Referring to FIG. 6, a reciprocating object removal threshold used whena reciprocating object removal filter distinguishes a person from areciprocating object can be varied, for example, in accordance withenvironment information such as the presence/absence of the wind and theintensity of the wind collected by the environment informationcollecting means 3. To be specific, for example, in an environment wherethe wind is not blowing, a tree or grass does not swing under theinfluence of the wind. Therefore, for example, in a case where theenvironment information collecting means 3 collects environmentinformation of no wind, the parameter changing means 42 is expected notto set a reciprocating object removal threshold and not to use areciprocating object removal filter. On the other hand, in anenvironment where the wind is blowing, a tree and grass swing under theinfluence of the wind. Therefore, the parameter changing means 42changes a reciprocating object removal threshold in accordance with thewind speed collected by the environment information collecting means 3,for example. To be specific, for example, in a case where theenvironment information collecting means 3 collects environmentinformation of the wind speed and it is determined the wind is strongbased on the collected environment information of the wind speed, theparameter changing means 42 is expected to change a reciprocating objectremoval threshold to be higher. On the other hand, in a case where it isdetermined that it is calm based on the environment information of thewind speed collected by the environment information collecting means 3,the parameter changing means 42 is expected to set a reciprocatingobject removal filter to be lower, or expected not to set areciprocating object removal threshold and not to apply a reciprocatingobject removal filter. Meanwhile, the parameter changing means 42 may beconfigured to set a reciprocating object removal threshold to be higherin stages in accordance with the intensity of the wind (the wind speed).Thus, change of a reciprocating object removal threshold by theparameter changing means 42 in accordance with the environmentinformation (the wind speed) collected by the environment informationcollecting means 3 makes it possible to accurately remove areciprocating object from the detection target. A preset threshold (astrong wind determination threshold, a calm determination threshold orthe like) may be used for determining whether the environmentinformation of the wind speed collected by the environment informationcollecting means 3 represents a strong wind or no wind. For example, ina case where the wind speed represented by the environment informationis more than the strong wind determination threshold, it is determinedwindy. In a case where the wind speed represented by the environmentinformation is equal to or less than the calm determination threshold,it is determined calm. Such a configuration makes it possible todetermine the intensity of the wind (whether it is windy or calm, forexample) based on the environment information of the wind speed.Further, including a plurality of thresholds enables determination ofthe intensity of the wind in stages based on the environment informationof the wind speed.

A shadow removal filter is a filter which regards a predetermined shadowas a moving object other than a person to be a detection target andexcludes the predetermined shadow from the detection target. Further, ashadow removal threshold is a threshold which is the criterion used whenthe shadow removal filter distinguishes the person from thepredetermined shadow. When the person of the detection target moves, ashadow thereof also moves together with the person. As a result, theshadow may interfere with detection of the person. Therefore, the shadowis regarded as a moving object which is not the person of the detectiontarget, and is excluded from the detection target. A shadow removalthreshold is, for example, a threshold which represents the amount(length, density or the like) of the shadow to be removed.

Referring to FIG. 7, a shadow removal threshold used when a shadowremoval filter distinguishes a person from a shadow can be changed, forexample, in accordance with environment information such as timecollected by the environment information collecting means 3. To bespecific, for example, the length of a shadow made around noon isdifferent from the length of a shadow made around dusk. Therefore, theamount such as length of a shadow to be removed is changed in accordancewith environment information such as time and latitude collected by theenvironment information collecting means 3. To be specific, for example,when time (environment information) collected by the environmentinformation collecting means 3 represents noon, the parameter changingmeans 42 is expected to set a shadow removal threshold to be low. On theother hand, for example, when time (environment information) collectedby the environment information collecting means 3 represents sunrisetime or sunset time, the parameter changing means 42 is expected to seta shadow removal threshold to be high. The environment informationcollecting means 3 may collect the latitude, the longitude, the date orthe like, other than time, as environment information. Thus, change of ashadow removal threshold by the parameter changing means 42 inaccordance with environment information collected by the environmentinformation collecting means 3 makes it possible to accurately remove ashadow. The abovementioned determination using environment informationof time is also enabled by using a preset threshold. For example, in acase where environment information of time represents within a range ofpreset time (a threshold representing a range of time), the parameterchanging means is expected to determine that it is sunrise or sunset.Moreover, a threshold for such a determination may be changed based onenvironment information of the latitude and longitude, environmentinformation representing season, and so on. Moreover, a shadow may bedifferent in intensity (density) depending on the weather, for example.Therefore, the parameter changing means 42 may be configured to becapable of changing the amount of a shadow to be removed depending onthe weather.

Thus, the video analyzing means 41 is capable of using various filtersfor removing a moving object other than a detection target object (aperson) from a detection target, and capable of using various movingobject distinction thresholds. Meanwhile, the video analyzing means 41can use various filters other than the ones described above. Forexample, the video analyzing means 41 may use a color tone correctionfilter, a sunshine variation filter which is a filter for detectingvariation of the whole environment, and so on. The video analyzing means41 may be configured to also change a moving object distinctionthreshold of the criterion used when the color tone correction filter orthe sunshine variation filter distinguishes a person from a movingobject other than the person, based on environment information collectedby the environment information collecting means 3. Moreover, the videoanalyzing mean 41 may include a filter for excluding a given value of awhite color parameter depending on the intensity of fog, for example.

Further, the video analyzing means 41 can be configured to detect amoving object by using a parameter other than the moving objectdetection parameter described above. For example, the video analyzingmeans 41 may be configured to regulate a contrast value according to adifference in weather.

Further, for example, referring to FIG. 8, there is a case where videodata acquired by the monitoring camera 2 includes target regionscorresponding to multiple kinds of environment information such as alight portion and a dark portion. In this case, for example, the videoanalyzing means 41 can be configured to separate a sensitivity thresholdfor the light portion and a sensitivity threshold for the dark portion.In other words, with respect to one video data, the video analyzingmeans 41 may use one moving object detection parameter for each kind, ormay use a plurality of moving object detection parameters for one kind.By determining the external environment of a place where the monitoringcamera 2 is installed by separating into a plurality of regions, itbecomes possible to perform change of a moving object detectionparameter more appropriate to the external environment.

Next, the operation of the video analysis system 1 according to thisexemplary embodiment will be described.

Firstly, an operation when the monitoring camera 2 acquires video data,the video analysis device 4 detects a person of a detection target fromthe acquired video data and the output device outputs the result of thedetection will be described.

Referring to FIG. 9, the monitoring camera 2 acquires video data at aplace where the monitoring camera 2 is installed (S101). Then, themonitoring camera 2 having acquired the video data processes the videodata into a predetermined format, and thereafter, transmits the videodata to the video analyzing means 41 included by the video analysisdevice 4 via the external network or the like.

Next, the video analyzing means 41 of the video analysis device 4receives the video data transmitted by the monitoring camera 2. Then,the video analyzing mean 41 detects a person moving in the acquiredvideo data and the trajectory of the moving person by using a movingobject detection parameter (S102). Then, the video analyzing means 41transmits the detection result (the moving person and the trajectory ofthe moving person) to the analysis result displaying means 43.

Subsequently, the analysis result displaying means 43 receives thedetection result transmitted by the video analyzing means 41. Then, theanalysis result displaying means 43 causes the output device such as themonitor connected with the analysis result displaying means 43 todisplay the analysis result (S103).

That is the operation when the monitoring camera 2 acquires video data,the video analyzing device 4 detects a person of a detection target fromthe acquired video data, and the output device outputs the detectionresult. Next, a detailed example of the operation when the videoanalyzing means 41 detects a moving person and the trajectory of themoving person from video data by using a moving object detectionparameter will be described.

Referring to FIG. 10, the video analyzing means 41 receives video datatransmitted by the monitoring camera 2. The video analyzing means 41then extracts successive image data from the received video data (S201).

Next, the video analyzing means 41 obtains, for example, a differencebetween image data of a previous frame and image data of a current frameand determines whether or not the image data of the current frame haschanged from the image data of the previous frame in accordance with asensitivity threshold (S202). Herein, a sensitivity threshold is one ofthe moving object detection parameters and is the criterion to determinehow to deal with a difference between image data of a previous frame andimage data of a current frame when the difference is detected (i.e.,determine whether there is a change or not). In other words, it varieswhether or not the video analyzing means 41 determines that image dataof a current frame has changed from image data of a previous frame, inaccordance with a sensitivity threshold as one of the moving objectdetection parameters.

Subsequently, by using a predetermined filter for removing a movingobject other than a person of a detection target from the detectiontarget, the video analyzing means 41 executes processing so as to detecta moving object other than a person as a moving object as little aspossible (S203). In this processing, the video analyzing means 41distinguishes a person from a moving object other than a person by usinga moving object distinction threshold. Herein, a moving objectdistinction threshold is one of the moving object detection parametersand, for example, a reciprocating object removal threshold and a shadowremoval threshold fall thereunder. The video analyzing means 41 alsochecks what the detected object is and detects a person. After that, thevideo analyzing means 41 acquires the trajectory of movement of theperson, and so on.

Thus, the video analyzing means 41 detects a person of a detectiontarget from video data by using the sensitivity threshold and the movingobject distinction threshold of the moving object detection parameters.Then, the video analyzing means 41 transmits the result of the detectionto the analysis result displaying means 43.

That is the operation when the video analyzing means 41 detects a movingperson and the trajectory of the moving person from video data by usinga moving object detection parameter. Next, an operation when a movingobject detection parameter is changed by the parameter changing means 42will be described.

Referring to FIG. 11, the environment information collecting means 3collects environment information representing the external environmentof a place where the monitoring camera 2 is installed (S301). Then, theenvironment information collecting means 3 transmits the collectedenvironment information to the parameter changing means 42 of the videoanalysis device 4. Meanwhile, the environment information collectingmeans 3 may collect environment information by using a physical sensorsuch as a GPS sensor, or may collect environment information on theInternet or the like.

Subsequently, the parameter changing means 42 receives the environmentinformation transmitted by the environment information collecting means3. Then, based on the acquired environment information, the parameterchanging means 42 changes a moving object detection parameter used whenthe video analyzing means 41 detects a person from video data (S302).Change of a moving object detection parameter by the parameter changingmeans 42 is performed, for example, by using a parameter set which is aset of moving object detection parameters previously determined inaccordance with a possible external environment. The parameter changingmeans 42 may be configured to change a moving object detection parameterfor each external environment represented by the environmentinformation.

That is the operation when a moving object detection parameter ischanged by the parameter changing means 42.

Thus, the video analysis system 1 according to this exemplary embodimentincludes the environment information collecting means 3 and theparameter changing means 42. With such a configuration, the videoanalysis system 1 is capable of collecting environment informationrepresenting the external environment of a place where the monitoringcamera 2 is installed, and changing a moving object detection parameterbased on the collected environment information. In other words, thevideo analysis system 1 is capable of changing a moving object detectionparameter used by the video analyzing means 41 in accordance with changeof the external environment of a place where the monitoring camera 2 isinstalled. As a result, it is possible to provide the video analysissystem 1 that prevents the accuracy of detection of a moving object frombeing affected even if the environment of a place where the monitoringcamera 2 is installed changes and video data changes.

Further, the video analysis system 1 according to this exemplaryembodiment includes a sensitivity threshold as one of the moving objectdetection parameters. Because the video analysis system 1 thus includesthe sensitivity threshold, the environment information collecting means3 and the parameter changing means 42, the video analysis system 1 iscapable of changing the sensitivity threshold in accordance with theexternal environment of a place where the monitoring camera 2 isinstalled. In other words, the video analysis system 1 is capable ofchanging the criterion for recognizing a disparity of image data when adifference of image data extracted from video data is obtained, inaccordance with the external environment. As a result, it is possible toprovide the video analysis system 1 that more reliably prevents theaccuracy of detection of a moving object from being affected even if theenvironment of a place where the monitoring camera 2 is installedchanges and video data changes.

Further, the video analysis system 1 according to this exemplaryembodiment includes a moving object distinction threshold as one of themoving object detection parameters. Because the video analysis system 1thus includes the moving object distinction threshold, the environmentinformation collecting means 3 and the parameter changing means 42, thevideo analysis system 1 is capable of changing a moving object detectionthreshold in accordance with the external environment of a place wherethe monitoring camera 2 is installed. In other words, the video analysissystem 1 is capable of changing the criterion used when a filter forremoving a moving object other than a detection target object from adetection target distinguishes the detection target object from themoving object other than the detection target object, in accordance withthe external environment. As a result, it is possible to more reliablyprovide the video analysis system 1 that prevents the accuracy ofdetection of a moving object from being affected even if the environmentof a place where the monitoring camera 2 is installed changes and videodata changes.

In this exemplary embodiment, the video analysis device 4 obtains adifference of image data extracted from video data and thereby detects aperson in the video data. However, the present invention is applicableto a case other than the abovementioned case of detecting a person byobtaining a difference. For example, the present invention is alsoapplicable to a case of detecting a person (a detection target object)by a method such as obtaining a motion vector and using patternrecognition.

Further, this exemplary embodiment has described a case where the videoanalyzing means 41 of the video analysis device 4 detects a person invideo data. However, a detection target object, which is a targetextracted from video data by the video analyzing means 41, is notlimited to a person. The video analyzing means 41 can detect varioustargets including a car and an animal such as a dog and a cat asdetection target objects.

Second Exemplary Embodiment

Next, a second exemplary embodiment of the present invention will bedescribed in detail referring to the drawings. In the second exemplaryembodiment, a video analysis system 6 including a parameter set, whichis a set of moving object detection parameters previously determined inaccordance with a possible external environment, will be described indetail. The video analysis system 6 according to this exemplaryembodiment has the partly same configuration as the configuration of thevideo analysis system 1 described in the first exemplary embodiment.Therefore, in this exemplary embodiment, a description will focus on adifferent part from the configuration of the first exemplary embodiment.

Referring to FIG. 12, the video analysis system 6 according to thesecond exemplary embodiment of the present invention has the monitoringcamera 2, the environment information collecting means 3, and a videoanalysis device 5. Further, the video analysis device 5 has the videoanalyzing means 41, the parameter changing means 42, the analysis resultdisplaying means 43, and a parameter set storing means 52. Further, theparameter changing means 42 has an optimum parameter determining means51, and a setting updating means 53. In other words, the video analysissystem 6 according to this exemplary embodiment is characterized byhaving the optimum parameter determining means 51, the parameter setstoring means 52, and the setting updating means 53. Herein, the samecomponents as those in the first exemplary embodiment will be described,denoted by the same reference numerals as those in the first exemplaryembodiment.

Hereinafter, a characteristic part of the second exemplary embodimentwill be described. In other words, the configuration of the optimumparameter determining means 51, the parameter set storing means 52 andthe setting updating means 53 included by the video analysis device 5will be described.

The optimum parameter determining means 51 has a function of comparingenvironment information collected by the environment informationcollecting means 3 with parameter sets stored by the parameter setstoring means 52 described later, and determining and selecting the mostappropriate parameter set to the acquired condition (the environmentinformation). The optimum parameter determining means 51 receivesenvironment information transmitted by the environment informationcollecting means 3. Then, the optimum parameter determining means 51compares the received environment information with (possible externalenvironments of) parameter sets stored by the parameter set storingmeans 52, and determines and selects the most appropriate parameter setto the environment information.

Selection of a parameter set by the optimum parameter determining means51 can be performed by using a table (a matrix) which defines adetermination rule, for example. Alternatively, the selection can beperformed by storing a combination having ever been experienced by theuser as preset values and using the preset values, for example. Thus,the optimum parameter determining means 51 can be configured to select aparameter set by using various means. Then, the optimum parameterdetermining means 51 transmits the parameter set selected by theabovementioned method to the setting updating means 53.

The parameter set storing means 52 is configured by a storage devicesuch as a hard disk and a RAM (Random Access Memory). The parameter setstoring means 52 is used for realization of an optimize functionpreviously included by the video analysis system 6.

The parameter set storing means 52 previously stores sets of movingobject detection parameters appropriate to possible externalenvironments, as parameter sets. Moving object detection parametersstored as a parameter set are, for example, control of the sensitivityto lightness, a filter for removing the swing of background objects liketrees due to the wind, and control of contrast with respect to adifference in weather. As mentioned above, the parameter sets stored bythe parameter set storing means 52 are compared with the externalenvironment by the optimum parameter determining means 51, and aparameter set corresponding to the most appropriate possible externalenvironment to the external environment is selected.

The parameter set storing means 52 can include a parameter setcorrecting means for correcting the parameter sets (e.g., values ofmoving object detection parameters thereof) stored by the parameter setstoring means 52.

The setting updating means 53 has a function of setting the mostappropriate parameter set to the external environment determined by theoptimum parameter determining means 51 dynamically in the video analysissystem 6. The setting updating means 53 receives a parameter set fromthe optimum parameter determining means 51. Then, the setting updatingmeans 53 compares current set values (moving object detection parametersbeing used by the video analyzing means 41) with the latest parameterset (received from the optimum parameter determining means 5). In a casewhere there is a difference between the current set values and thelatest parameter set, the setting updating means 53 changes the movingobject detection parameters being used by the video analyzing means 41with the parameter set. On the other hand, in a case where there is nota difference between the current set values and the latest parameterset, the setting updating means 53 does not change the moving objectdetection parameters but discards the parameter set, for example.

That is the characteristic configuration of the video analysis system 6according to this exemplary embodiment. Next, an operation when changingmoving object detection parameters, which is a characteristic operationof the video analysis system 6 according to this exemplary embodiment,will be described.

Referring to FIG. 13, the environment information collecting means 3collects environment information representing the external environmentof a place where the monitoring camera 2 is installed (S401). Then, theenvironment information collecting means 3 transmits the collectedenvironment information to the optimum parameter determining means 51 ofthe video analysis device 4. The environment information collectingmeans 3 may collect environment information by using a physical sensorsuch as a GPS sensor, or may collect environment information on theInternet or the like.

Next, the optimum parameter determining mean 51 receives the environmentinformation transmitted by the environment information collecting means3. Then, the optimum parameter determining means 51 compares theexternal environment represented by the received environment informationwith possible external environments corresponding to the parameter setsstored by the parameter set storing means 52 (S402). Then, the optimumparameter determining means 51 selects the most appropriate possibleexternal environment to the external environment represented by theenvironment information (S403), and acquires a parameter setcorresponding to the selected possible external environment from theparameter set storing means 52 (S404). After that, the optimum parameterdetermining means 51 transmits the acquired parameter set to the settingupdating means 53.

Subsequently, the setting updating means 53 receives the parameter settransmitted by the optimum parameter determining means 51. Then, thesetting updating means 53 compares moving object detection parameters(current set values) used when the video analyzing means 41 detects amoving object in video data, with the received parameter set (the latestparameter set) (S405). Then, in a case where there is a differencebetween the current set values and the latest parameter set (YES atS405), the setting updating means 53 changes the moving object detectionparameters used by the video analyzing means 41 with the parameter set(S406). On the other hand, in a case where there is not a differencebetween the current set values and the latest parameter set (NO at stepS405), the setting updating means 53 does not change the moving objectdetection parameters but discards the parameter set, for example. Inthis case, the setting updating means 53 waits until environmentinformation is collected by the environment information collecting means3 again, and determines whether or not to change moving object detectionparameters.

That is the operation when the video analysis system 6 changes movingobject detection parameters.

Thus, the video analysis system 6 according to this exemplary embodimentincludes the optimum parameter determining means 51, the parameter setstoring means 52, and the setting updating means 53. With such aconfiguration, the video analysis system 6 is capable of selecting themost appropriate possible external environment to an externalenvironment represented by environment information collected by theenvironment information collecting means 3. Moreover, the video analysissystem 6 is capable of changing moving object detection parameters witha parameter set appropriate to the selected possible externalenvironment. As a result, it becomes unnecessary to consider change ofeach moving object detection parameter in accordance with an externalenvironment represented by the environment information collected by theenvironment information collecting means 3, and it is possible to reduceload of changing moving object detection parameters

Next, a third exemplary embodiment of the present invention will bedescribed in detail referring to the attached drawings. The thirdexemplary embodiment will describe the overview of the configuration ofa video analysis system 7.

Third Exemplary Embodiment

Referring to FIG. 14, the video analysis system 7 according to the thirdexemplary embodiment of the present invention has a video data acquiringmeans 71, a moving object detecting means 72, an environment informationcollecting means 73, and a parameter changing means 74.

The video data acquiring means 71 has a function of acquiring videodata. The video data acquiring means 71 is a monitoring camera or thelike and is installed at the airport, at an oil plant, on the street,and so on. Moreover, the video data acquiring means 71 is connected tothe moving object detecting means 72 via a network or the like, andvideo data acquired by the video data acquiring means 71 is transmittedto the moving object detecting means 72.

The moving object detecting means 72 has a function of detecting, invideo data acquired by the video data acquiring means 71, a movingobject moving in the video data by using a moving object detectionparameter, which is a parameter for detecting a moving object. Themoving object detecting means 72 receives video data transmitted by thevideo data acquiring means 71. Subsequently, the moving object detectingmeans 72 detects a moving object moving in the video data by using amoving object detection parameter. After that, the moving objectdetecting means 72 outputs the result of the detection to an externaldevice such as a monitor.

Herein, a moving object detection parameter is a sensitivity threshold,a moving object distinction threshold such as a reciprocating objectremoval threshold and a shadow removal threshold, or the like. Moreover,a moving object detection parameter is properly changed based onenvironment information collected by the environment informationcollecting means 73 as described later.

The environment information collecting means 73 has a function ofcollecting environment information representing the external environmentof a place where the video data acquiring means 71 is installed. Theenvironment information collecting means 73 is, for example, a calendar,a Web information collecting means, and various sensors such as a GPSsensor. The environment information collecting means 73 is connected tothe parameter changing means 74, and environment information collectedby the environment information collecting means 73 is transmitted to theparameter changing means 74.

The parameter changing means 74 has a function of changing a movingobject detection parameter used when the moving object detecting means72 detects a moving object in video data, based on environmentinformation collected by the environment information collecting means73. The parameter changing means 74 receives environment informationfrom the environment information collecting means 73. Then, theparameter changing means 74 changes a moving object detection parameterbased on (an external environment represented by) the acquiredenvironment information (e.g., so as to optimize the moving objectdetection parameter for the external environment). Thus, a moving objectdetection parameter used when the moving object detecting means 72detects a moving object in video data is changed based on environmentinformation collected by the environment information collecting means73.

Thus, the video analysis system 7 according to this exemplary embodimentincludes the environment information collecting means 73 and theparameter changing means 74. With such a configuration, the videoanalysis system 7 is capable of collecting environment informationrepresenting the external environment of a place where the video imageacquiring means 71 is installed, and changing a moving object detectionparameter based on the collected environment information. In otherwords, the video analysis system 7 is capable of changing a movingobject detection parameter used by the moving object detecting means 72in accordance with change of the external environment of a place wherethe video data acquiring means 71 is installed. As a result, it ispossible to provide the video analysis system 7 that prevents theaccuracy of detection of a moving object from being affected even if theenvironment of a place where the video data acquiring means 71 isinstalled changes and video data changes.

Next, a fourth exemplary embodiment of the present invention will bedescribed in detail referring to the drawings. The fourth exemplaryembodiment describes the configuration overview of a video analysisdevice 8.

Fourth Exemplary Embodiment

Referring to FIG. 15, the video analysis device 8 according to thefourth exemplary embodiment of the present invention has a video dataacquisition part 81, a moving object detection part 82, an environmentinformation collection part 83, and a parameter changing part 84.

The video data acquisition part 81 has a function of acquiring data of avideo image shot by a monitoring camera installed outside or the like.The video data acquisition part 81 is connected to a video dataacquiring means such as a monitoring camera installed at the airport, atan oil plant, on the street, and so on, via a network or the like, andacquires video data acquired by the video data acquiring means. Thevideo data acquisition part 81 having acquired the video data transmitsthe acquired video data to the moving object detection part 82.

The moving object detection part 82 has a function of detecting, invideo data acquired by the video data acquisition part 81, a movingobject moving in the video data by using a moving object detectionparameter, which is a parameter for detecting a moving object. Themoving object detection part 82 receives video data transmitted by thevideo data acquisition part 81. Subsequently, the moving objectdetection part 82 detects a moving object moving in the video data byusing a moving object detection parameter. After that, the moving objectdetection part 82 outputs the result of the detection to an externaldevice such as a monitor.

Herein, a moving object detection parameter is a sensitivity threshold,a moving object distinction threshold such as a reciprocating objectremoval threshold and a shadow removal threshold, or the like. Moreover,a moving object detection parameter is properly changed based onenvironment information collected by the environment informationcollection part 83 as described later.

The environment information collection part 83 has a function ofacquiring environment information representing the external environmentof a place where video data acquired by the video data acquisition part81 has been acquired. The environment information collection part 83has, for example, a calendar and a Web information collecting means, andcollects environment information from the calendar, the Web, and so on.Moreover, the environment information collection part 83 is connectedwith various sensors such as a GPS sensor which acquires environmentinformation such as meteorological information (time, latitude andlongitude, weather, wind speed, and so on) of the place where the videodata has been acquired. The environment information collection part 83collects environment information from the various sensors. Then, theenvironment information collecting part 83 having collected environmentinformation transmits the collected environment information to theparameter changing part 84.

The parameter changing part 84 has a function of changing a movingobject detection parameter used when the moving object detection part 82detects a moving object in video data, based on environment informationcollected by the environment information collection part 83. Theparameter changing part 84 receives environment information from theenvironment information collection part 83. Then, the parameter changingpart 84 changes a moving object detection parameter based on (anexternal environment represented by) the acquired environmentinformation (e.g., so as to optimize a moving object detection parameterfor the external environment). Consequently, a moving object detectionparameter used when the moving object detection part 82 detects a movingobject in video data is changed based on environment informationcollected by the environment information collection part 83.

Thus, the video analysis device 8 according to this exemplary embodimentincludes the environment information collection part 83 and theparameter changing part 84. With such a configuration, the videoanalysis system 8 is capable of collecting environment informationrepresenting the external environment of a place where video dataacquired by of the video image acquisition part 81 has been acquired,and changing a moving object detection parameter based on the collectedenvironment information. In other words, the video analysis device 8 iscapable of changing a moving object detection parameter used by themoving object detection part 82 in accordance with change of theexternal environment of a place where video data acquired by the videodata acquisition part 81 has been acquired. As a result, it is possibleto provide the video analysis device 8 that prevents the accuracy ofdetection of a moving object from being affected even if the environmentof a place where video data acquired by the video data acquisition part81 has been acquired changes and video data changes.

The abovementioned video analysis device 8 can be realized by installinga predetermined program in the video analysis device 8. To be specific,a program as another aspect of the present invention is a computerprogram for causing a video analysis device to function as: a video dataacquisition part which acquires video data acquired by an externaldevice from the external device; a moving object detection part whichdetects, in video data acquired by the video data acquisition part, amoving object moving in the video data by using a moving objectdetection parameter, which is a parameter for detecting a moving object;an environment information collection part which collects environmentinformation representing the external environment of a place where theexternal device having acquired the video data; and a parameter changingpart which changes a moving object detection parameter used when themoving object detection part detects a moving object, based on theenvironment information acquired by the environment informationcollection part.

Further, a method for video analysis executed by operation of theabovementioned video analysis device 8 is a method including: collectingenvironment information representing the external environment of a placewhere an external device acquiring video data is installed; changing amoving object detection parameter used when detecting a moving object invideo data, based on the collected environment information; anddetecting, in video data acquired by an external device, the movingobject moving in the video data by using the changed moving objectdetection parameter.

The invention of a program or a video analysis method having theabovementioned configurations has the same actions as the video analysisdevice 8, and therefore, can achieve the object of the present inventiondescribed above.

Supplementary Notes

The whole or part of the exemplary embodiments disclosed above can bedescribed as the following supplementary notes. Below, the outline ofthe video analysis system and so on according to the present inventionwill be described. However, the present invention is not limited to thefollowing configurations.

Supplementary Note 1

A video analysis system comprising:

a video data acquiring means for acquiring video data;

a moving object detecting means for detecting a moving object from videodata by using a moving object detection parameter, the video data havingbeen acquired by the video data acquiring means, the moving objectdetection parameter being a parameter for detecting a moving object;

an environment information collecting means for collecting environmentinformation representing an external environment of a place where thevideo data acquiring means is installed; and

a parameter changing means for changing the moving object detectionparameter on a basis of the environment information collected by theenvironment information collecting means, the moving object detectionparameter being used when the moving object detecting means detects themoving object.

According to this configuration, the video analysis system includes theenvironment information collecting means and the parameter changingmeans. Such a configuration enables the video analysis system to collectenvironment information representing the external environment of a placewhere the video data acquiring means is installed and change the movingobject detection parameter based on the collected environmentinformation. In other words, such a configuration enables the videoanalysis system to change the moving object detection parameter used bythe moving object detecting means in accordance with change of theexternal environment of the place where the video data acquiring meansis installed. As a result, it is possible to provide the video analysissystem which prevents the accuracy of detection of a moving object frombeing affected even when the environment of the place where the videodata acquiring means is installed changes and video data changes.

Supplementary Note 2

The video analysis system according to Supplementary Note 1, wherein:

the moving object detecting means is configured to detect the movingobject by obtaining a difference of image data extracted from the videodata and includes a sensitivity threshold as one of moving objectdetection parameters, the sensitivity threshold being a predeterminedthreshold to become a criterion for recognizing a disparity betweenimage data of a previous frame and image data of a current frame; and

the parameter changing means changes the sensitivity threshold on abasis of the environment information collected by the environmentinformation collecting means, the sensitivity threshold being one of themoving object detection parameters.

According to this configuration, the video analysis system includes thesensitivity threshold as one of the moving object detection parameters.Such a configuration enables the video analysis system to change thesensitivity threshold in accordance with the external environment of aplace where the video data acquiring means is installed. In other words,such a configuration enables the video analysis system to change thecriterion for recognizing a disparity of image data when obtaining adifference of image data extracted from video data, in accordance withthe external environment. As a result, it is possible to provide thevideo analysis system 1 which more reliably prevents the accuracy ofdetection of a moving object from being affected even when theenvironment of the place where the video data acquiring means isinstalled changes and video data changes.

Supplementary Note 3

The video analysis system according to Supplementary Note 1 or 2,wherein:

the moving object detecting means is configured to use a predeterminedfilter when detecting the moving object from the video data and includesa moving object distinction threshold as one of moving object detectionparameters, the predetermined filter being for removing a moving objectother than a detection target object from a detection target, thedetection target object being a target to be detected, the moving objectdistinction threshold being a predetermined threshold used when thepredetermined filter distinguishes the detection target object from themoving object other than the detection target object; and

the parameter changing means changes the moving object distinctionthreshold on a basis of the environment information collected by theenvironment information collecting means, the moving object distinctionthreshold being one of the moving object detection parameters.

According to this configuration, the video analysis system includes themoving object distinction threshold as one of the moving objectdetection parameters. Such a configuration enables the video analysissystem 1 to change the moving object detection threshold in accordancewith the external environment of a place where the monitoring camera 2is installed. In other words, such a configuration enables the videoanalysis system 1 to change the criterion used when the filter forremoving a moving object other than a detection target object from thetarget of detection distinguishes a detection target object from amoving object other than the detection target object, in accordance withthe external environment. As a result, it is possible to provide thevideo analysis system 1 which more reliably prevents the accuracy ofdetection of a moving object from being affected even when theenvironment of the place where the monitoring camera is installedchanges and video data changes.

Supplementary Note 4

The video analysis system according to Supplementary Note 3, wherein:

the moving object detecting means is configured to use a reciprocatingobject removal filter when detecting the moving object from the videodata and includes a reciprocating object removal threshold as one of themoving object distinction parameters, the reciprocating object removalfilter being configured to regard a reciprocating object as the movingobject other than the detection target object and remove thereciprocating object from the detection target, the reciprocating objectperforming predetermined reciprocation, the predetermined reciprocationbeing a repetitive movement, the reciprocating object removal thresholdbeing a threshold used when the reciprocating object removal filterdistinguishes the detection target object from the reciprocating object;and

the parameter changing means changes the reciprocating object removalthreshold on a basis of the environment information collected by theenvironment information collecting means, the reciprocating objectremoval threshold being one of the moving object detection parameters.

According to this configuration, the video analysis system includes thereciprocating object removal threshold as one of the moving objectdistinction thresholds. Such a configuration enables the video analysissystem to change the reciprocating object removal threshold inaccordance with the external environment of a place where the video dataacquiring means is installed. In other words, such a configurationenables the video analysis system to change the criterion used when thefilter for removing a moving object other than a detection targetobject, that is, removing a reciprocating object from the target ofdetection distinguishes a detection target object from a moving objectother than the detection target object, that is, from a reciprocatingobject, in accordance with the external environment. As a result, it ispossible to provide the video analysis system which more reliablyprevents the accuracy of detection of a moving object from beingaffected even when the environment of the place where the video dataacquiring means is installed changes and video data changes.

Supplementary Note 5

The video analysis system according to Supplementary Note 4, wherein:

the environment information collecting means is configured to collectwind speed information as the environment information, the wind speedinformation representing a wind speed; and

the parameter changing means changes the reciprocating object removalthreshold in accordance with the wind speed represented by the windspeed information collected by the environment information collectingmeans, the reciprocating object removal threshold being one of themoving object detection parameters.

Supplementary Note 6

The video analysis system according to any of Supplementary Notes 3 to5, wherein:

the moving object detecting means is configured to use a shadow removalfilter when detecting the moving object from the video data and includesa shadow removal threshold as one of moving object distinctionparameters, the shadow removal filter being configured to regard apredetermined shadow as the moving object other than the detectiontarget object and remove the predetermined shadow from the detectiontarget, the shadow removal threshold being a threshold used when theshadow removal filter distinguishes the detection target object from thepredetermined shadow; and

the parameter changing means changes the shadow removal threshold on abasis of the environment information collected by the environmentinformation collecting means, the shadow removal threshold being one ofthe moving object detection parameters.

According to this configuration, the video analysis system includes theshadow removal threshold as one of the moving object distinctionthresholds. Such a configuration enables the video analysis system tochange the shadow removal threshold in accordance with the externalenvironment of a place where the video data acquiring means isinstalled. In other words, such a configuration enables the videoanalysis system to change the criterion used when the filter forremoving a moving object other than a detection target object, that is,removing a shadow from the target of detection distinguishes a detectiontarget object from a moving object other than the detection targetobject, that is, from a shadow, in accordance with the externalenvironment.

Supplementary Note 7

The video analysis system according to Supplementary Note 6, wherein:

the environment information collecting means is configured to collecttime information as the environment information, the time informationrepresenting time; and

the parameter changing means changes the shadow removal threshold inaccordance with the time represented by the time information collectedby the environment information collecting means, the shadow removalthreshold being one of the moving object detection parameters.

Supplementary Note 8

The video analysis system according to any of Supplementary Notes 1 to7, further comprising a parameter set storing means for storing apredetermined set of the moving object detection parameters as aparameter set, the predetermined set of the moving object detectionparameters being corresponding to a possible external environment,

wherein the parameter changing means changes the moving object detectionparameters, on a basis of the environment information collected by theenvironment information collecting means, by using the parameter setcorresponding to the external environment represented by the environmentinformation.

According to this configuration, the video analysis system includes theparameter set storing means, and is configured to change the movingobject detection parameters by using a parameter set corresponding to anexternal environment represented by environment information. Such aconfiguration enables the video analysis system to select a possibleexternal environment appropriate to the external environment representedby the environment information. Moreover, such a configuration enablesthe video analysis system to change the moving object detectionparameters by using a parameter set corresponding to the selectedpossible external environment. As a result, it is not necessary toconsider change of the individual moving object detection parameters inaccordance with the external environment represented by the environmentinformation, and it is possible to achieve reduction of the load forchanging the moving object detection parameters.

Supplementary Note 9

The video analysis system according to any of Supplementary Notes 1 to8, wherein the environment information is at least one of: luminance;time and date; meteorological information; and latitude and longitude.

Supplementary Note 10

A video analysis device comprising:

a video data acquisition part configured to acquire video data from anexternal device, the video data having been acquired by the externaldevice;

a moving object detection part configured to detect a moving object fromvideo data by using a moving object detection parameter, the video datahaving been acquired by the video data acquisition part, the movingobject detection parameter being a parameter for detecting a movingobject;

an environment information collection part configured to collectenvironment information representing an external environment of a placewhere the external device having acquired the video data is installed;and

a parameter changing part configured to change the moving objectdetection parameter on a basis of the environment information collectedby the environment information collection part, the moving objectdetection parameter being used when the moving object detection partdetects the moving object.

Supplementary Note 11

The video analysis device according to Supplementary Note 10, wherein:

the moving object detection part is configured to detect the movingobject by obtaining a difference of image data extracted from the videodata and includes a sensitivity threshold as one of moving objectdetection parameters, the sensitivity threshold being a predeterminedthreshold to become a criterion for recognizing a disparity betweenimage data of a previous frame and image data of a current frame; and

the parameter changing part changes the sensitivity threshold on a basisof the environment information of the place where the external devicehaving acquired the video data is installed, the sensitivity thresholdbeing one of the moving object detection parameters.

Supplementary Note 12

The video analysis device according to Supplementary Note 10 or 11,wherein:

the moving object detection part is configured to use a predeterminedfilter when detecting the moving object from the video data and includesa moving object distinction threshold as one of moving object detectionparameters, the predetermined filter being for removing a moving objectother than a detection target object from a detection target, thedetection target object being a target of detection, the moving objectdistinction threshold being a predetermined threshold used when thepredetermined filter distinguishes the detection target object from themoving object other than the detection target object; and

the parameter changing part changes the moving object distinctionthreshold on a basis of the environment information of the place wherethe external device having acquired the video data is installed, themoving object distinction threshold being one of the moving objectdetection parameters.

Supplementary Note 13

The video analysis device according to Supplementary Note 12, wherein:

the moving object detection part is configured to use a reciprocatingobject removal filter when detecting the moving object from the videodata and includes a reciprocating object removal threshold as one of themoving object distinction parameters, the reciprocating object removalfilter being configured to regard a reciprocating object as the movingobject other than the detection target object and remove thereciprocating object from the detection target, the reciprocating objectperforming predetermined reciprocation, the predetermined reciprocationbeing a repetitive movement, the reciprocating object removal thresholdbeing a threshold used when the reciprocating object removal filterdistinguishes the detection target object from the reciprocating object;and

the parameter changing part changes the reciprocating object removalthreshold on a basis of the environment information of the place wherethe external device having acquired the video data is installed, thereciprocating object removal threshold being one of the moving objectdetection parameters.

Supplementary Note 14

The video analysis device according to Supplementary Note 12 or 13,wherein:

the moving object detection part is configured to use a shadow removalfilter when detecting the moving object from the video data and includesa shadow removal threshold as one of the moving object distinctionparameters, the shadow removal filter being configured to regard apredetermined shadow as the moving object other than the detectiontarget object and remove the predetermined shadow from the detectiontarget, the shadow removal threshold being a threshold used when theshadow removal filter distinguishes the detection target object from thepredetermined shadow; and

the parameter changing part changes the shadow removal threshold on abasis of the environment information of the place where the externaldevice having acquired the video data is installed, the shadow removalthreshold being one of the moving object detection parameters.

Supplementary Note 15

The video analysis device according to any of Supplementary Notes 10 to14, further comprising a parameter set storage part configured to storea predetermined set of the moving object detection parameters as aparameter set, the predetermined set of the moving object detectionparameters being corresponding to a possible external environment,

wherein the parameter changing part changes the moving object detectionparameters, on a basis of the environment information of the place wherethe external device having acquired the video data is installed, byusing the parameter set corresponding to an external environmentrepresented by the environment information.

Supplementary Note 16

The video analysis device according to any of Supplementary Notes 10 to15, wherein the environment information is at least one of: luminance;time and date; meteorological information; and latitude and longitude.

Supplementary Note 17

A video analysis method comprising:

collecting environment information and changing a moving objectdetection parameter on a basis of the collected environment information,the environment information representing an external environment of aplace where an external device acquiring video data is installed, themoving object detection parameter being used when detecting a movingobject from the video data; and

detecting the moving object from the video data by using the changedmoving object detection parameter, the video data being acquired fromthe external device.

Supplementary Note 18

The video analysis method according to Supplementary Note 17,comprising:

changing a sensitivity threshold on a basis of the environmentinformation of the place where the external device acquiring the videodata is installed, the sensitivity threshold being used as one of movingobject detection parameters, the sensitivity threshold being apredetermined threshold to become a criterion for recognizing adisparity between image data of a previous frame and image data of acurrent frame; and

obtaining a difference of image data extracted from the video data byusing the changed sensitivity threshold, and detecting the movingobject.

Supplementary Note 19

The video analysis method according to Supplementary Note 18,comprising:

changing a moving object distinction threshold on a basis of theenvironment information of the place where the external device acquiringthe video data is installed, the moving object distinction thresholdbeing used as one of the moving object detection parameters, the movingobject distinction threshold being a predetermined threshold used whendistinguishing a detection target object to become a target of detectionfrom a moving object other than the detection target object; and

by using the changed moving object distinction threshold, removing themoving object other than the detection target object from a detectiontarget when detecting the moving object from the video data.

Supplementary Note 20

The video analysis method according to any of Supplementary Notes 17 to19, wherein the environment information is at least one of: luminance;time and date; meteorological information; and latitude and longitude.

Supplementary Note 21

A computer program including instructions for causing a video analysisdevice to function as:

a video data acquisition part configured to acquire video data from anexternal device, the video data being acquired by the external device;

a moving object detection part configured to detect a moving object fromvideo data by using a moving object detection parameter, the movingobject moving in the video data, the video data being acquired by thevideo data acquisition part, the moving object detection parameter beinga parameter for detecting a moving object;

an environment information collection part configured to collectenvironment information representing an external environment of a placewhere the external device having acquired the video data is installed;and

a parameter changing part configured to change the moving objectdetection parameter on a basis of the environment information acquiredby the environment information collection part, the moving objectdetection parameter being used when the moving object detection partdetects the moving object.

The program described in the exemplary embodiments and the supplementarynote is stored in the storage device or recorded on a computer-readablemedium. For example, the recording medium is a portable medium such as aflexible disk, an optical disk, a magnet-optical disk and asemiconductor memory.

Although the present invention has been described above referring to theexemplary embodiments, the present invention is not limited to theexemplary embodiments. The configurations and details of the presentinvention can be changed and modified in various manners that can beunderstood by one skilled in the art within the scope of the presentinvention.

This application is based upon and claims the benefit of priority fromJapanese patent application No. 2014-026465, filed on Feb. 14, 2014, thedisclosure of which is incorporated herein in its entirety by reference.

Description of Reference Numerals

-   1, 6, 7 video analysis system-   2 monitoring camera-   3 environment information collecting means-   31 calendar-   32 Web-   33 various sensors-   4, 5 video analysis device-   41 video analyzing means-   42 parameter changing means-   43 analysis result displaying means-   51 optimum parameter determining means-   52 parameter set storing means-   53 setting updating means-   71 video data acquiring means-   72 moving object detecting means-   73 environment information collecting means-   74 parameter changing means-   81 video data acquisition part-   82 moving object detection part-   83 environment information collection part-   84 parameter changing part

1. A video analysis system comprising: at least one memory storinginstructions; and at least one processor executing the instructions toperform; acquiring video data acquired at a predetermined location;detecting a moving object from the video data by using a moving objectdetection parameter, the moving object detection parameter being aparameter for detecting a moving object; and collecting environmentinformation for specifying one or more causes making a shadow; whereinthe at least one processor further performs; removing the shadow fromthe moving object, using a shadow removal threshold to distinguish themoving object from the shadow; and changing the shadow removal thresholdin accordance with the environment information.
 2. The video analysissystem according to claim 1, wherein the shadow removal thresholdrepresents an amount indicating a length or a density of the shadow. 3.The video analysis system according to claim 1, wherein the environmentinformation includes the time or the date when the video data isacquired.
 4. The video analysis system according to claim 1, wherein theenvironment information includes latitude and longitude where the videodata is acquired.
 5. The video analysis system according to claim 1,wherein the environment information includes the weather when the videodata is acquired.
 6. The video analysis system according to claim 1,wherein the environment information includes the luminance collectedwhen the video data is acquired.
 7. A video analysis method comprising:acquiring video data acquired at a predetermined location; detecting amoving object from the video data by using a moving object detectionparameter, the moving object detection parameter being a parameter fordetecting a moving object; and collecting environment information forspecifying one or more causes making a shadow; wherein the at least oneprocessor further performs; removing the shadow from the moving object,using a shadow removal threshold to distinguish the moving object fromthe shadow; and changing the shadow removal threshold in accordance withthe environment information.
 8. The video analysis method according toclaim 7, wherein the shadow removal threshold represents an amountindicating a length or a density of the shadow.
 9. The video analysismethod according to claim 7, wherein the environment informationincludes the time or the date when the video data is acquired.
 10. Thevideo analysis method according to claim 7, wherein the environmentinformation includes latitude and longitude where the video data isacquired.
 11. The video analysis method according to claim 7, whereinthe environment information includes the weather when the video data isacquired.
 12. The video analysis method according to claim 7, whereinthe environment information includes the luminance collected when thevideo data is acquired.
 13. A non-transitory computer-readable storagemedium storing a program causing a computer to perform: acquiring videodata acquired at a predetermined location; detecting a moving objectfrom the video data by using a moving object detection parameter, themoving object detection parameter being a parameter for detecting amoving object; and collecting environment information for specifying oneor more causes making a shadow; wherein the at least one processorfurther performs; removing the shadow from the moving object, using ashadow removal threshold to distinguish the moving object from theshadow; and changing the shadow removal threshold in accordance with theenvironment information.
 14. The non-transitory computer-readablestorage medium according to claim 13, wherein the shadow removalthreshold represents an amount indicating a length or a density of theshadow.
 15. The non-transitory computer-readable storage mediumaccording to claim 13, wherein the environment information includes thetime or the date when the video data is acquired.
 16. The non-transitorycomputer-readable storage medium according to claim 13, wherein theenvironment information includes latitude and longitude where the videodata is acquired.
 17. The non-transitory computer-readable storagemedium according to claim 13, wherein the environment informationincludes the weather when the video data is acquired.
 18. Thenon-transitory computer-readable storage medium according to claim 13,wherein the environment information includes the luminance collectedwhen the video data is acquired.